Comparison of a novel viscous platelet additive solution and plasma: preparation and <i>in vitro</i> storage parameters of buffy‐coat‐derived platelet concentrates
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: We developed a viscous platelet additive solution (PAS) based on MacoPharma's SSP+ but containing hydroxyethyl starch to address the poor osmotic balance and low yield associated with conventional PAS for the storage of buffy-coat platelet concentrates (PC). MATERIALS AND METHODS: Pools of four buffy-coats were made into leucoreduced PCs (n = 5) suspended either in plasma or viscous PAS. After determination of platelet recoveries, the PCs were stored under standard conditions. On days 1, 2, 3, 5, 7 and 9, PCs were tested for mean platelet volume, platelet concentration, soluble protein concentration, CD62 expression, platelet morphology, partial pressure of oxygen and partial pressure of carbon dioxide, glucose and lactate concentration, pH, extent of shape change, and hypotonic shock response (HSR). RESULTS: Platelets were prepared with greater ease using the viscous PAS and had improved platelet yield. PCs stored in either plasma or viscous PAS displayed similar storage characteristics to day 9. On days 7 and 9 of storage, platelets stored in viscous PAS displayed significantly lower (P < 0.05) CD62 expression and higher HSR scores than those stored in plasma. CONCLUSION: Alteration of the viscosity of PAS improves platelet recovery during processing and may prolong platelet quality at the later stages of storage.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".